Evaluation of Fatigue Characteristics of Aluminum Alloys and Mechanical Components Using Extreme Value Statistics and C-specimens

In this study, the fatigue characteristics of aluminum alloys and mechanical components were investigated. To evaluate the effect of forging, fatigue specimens with the same chemical compositions were prepared from billets and forged mechanical components. To evaluate the cleanliness of the aluminum alloys, the cross-sectional area of specimens was observed, and the maximum inclusion sizes were obtained using extreme value statistics. Rotary bending fatigue tests were performed, and the fracture surfaces of the specimens were analyzed. The results show that the forging process not only elevated the fatigue strength but also reduced the scatter of the fatigue life of aluminum alloys. The fatigue characteristics of C-specimens were obtained to develop finite-element method (FEM) models. With the intrinsic fatigue properties and strain–life approach, the FEM analysis results agreed well with the test results.

Early Crack Propagation in Single Tooth Bending Fatigue: Combination of Finite Element Analysis and Critical-Planes Fatigue Criteria

Mechanical components, such as gears, are usually subjected to variable loads that induce multiaxial non-proportional stress states, which in turn can lead to failure due to fatigue. However, the material properties are usually available in the forms of bending or shear fatigue limits. Multiaxial fatigue criteria can be used to bridge the gap between the available data and the actual loading conditions. However, different criteria could lead to different results. The main goal of this paper is to evaluate the accuracy of different criteria applied to real mechanical components. With respect to this, five different criteria based on the critical plane concept (i.e., Findley, Matake, McDiarmid, Papadopoulos, and Susmel) have been investigated. These criteria were selected because they not only assess the level of damage, but also predict the direction of crack propagation just after nucleation. Therefore, measurements (crack position and direction) on different fractured gear samples tested via Single Tooth Bending Fatigue (STBF) tests on two gear geometries were used as reference. The STBF configuration was numerically simulated via Finite Elements (FE) analyses. The results of FE were elaborated based on the above-mentioned criteria. The numerical results were compared with the experimental ones. The result of the comparison showed that all the fatigue criteria agree in identifying the most critical point. The Findley and Papadopulus criteria proved to be the most accurate in estimating the level of damage. The Susmel criterion turns out to be the most conservative one. With respect to the identification of the direction of early propagation of the crack, the Findley criterion revealed the most appropriate.

Improving mechanical properties of the UIC test bench

Brakes are one of the most important components of vehicles. This is due to their function of decelerating, regulating vehicle speed and keeping vehicles stationary. The correct function and reliability of this system is essential for safe operation and vehicles driving. In our case, we deal with the brakes of rail vehicles. As trainsets achieve higher weights and speeds, great emphasis is also placed on improving the friction components of brake systems, which must meet the strict parameters set by the International Union of Railways (UIC) and must be tested on specialized approved test benches, before being put into service. As the demands on the development of friction components increase, so do the demands on their testing. From this point of view, there is necessary constant improvement in the measuring lane of the brake bench. It is necessary to improve the measuring and control technology as well as the mechanical components. This paper deals with the study of mechanical components in terms of operational dynamics. The main idea of the work is to create a virtual model of the brake bench in order to simulate the operating states and determine the critical modes with a possible adverse impact on the course of measurement and control. During the measurement, the monitored parameter is an important simulated mass, which must meet a precisely determined tolerance for the success of the measurement.

Updatable Probabilistic Evaluation of Failure Rates of Mechanical Components in Power Take-Off Systems of Tidal Stream Turbines

This paper presents a method for the probabilistic evaluation of the failure rates of mechanical components in a typical power take-off (PTO) system of a horizontal-axis tidal stream turbine (HATT). The method is based on a modification of the method of the influence factors, when base failure rates, relevant influence factors and, subsequently, resulting failure rates are treated as random variables. The prior (i.e., initial) probabilistic distribution of the failure rates of a HATT component is generated using data for similar components from other industries, while taking into account actual characteristics of the component and site-specific operating and environmental conditions of the HATT. A posterior distribution of the failure rate is estimated numerically based on a Bayesian approach as new information about the component performance in an operating HATT becomes available. The posterior distribution is then employed to obtain the updated mean and lower and upper confidence limits of the failure rate. The proposed method is illustrated by applying it to the evaluation of the failure rates of two key components of the PTO system of a typical HATT—main seal and main bearing. In particular, it is shown that uncertainty associated with the method itself has a major influence on the failure rate evaluation. The proposed method is useful for the reliability assessment of both PTO designs of new HATTs and PTO systems of operating HATTs.

Estimate the useful life for a heating, ventilation, and air conditioning system on a high-speed train using failure models

<p class="Abstract">Heating, ventilation, and air conditioning (HVAC) is a widely used system used to guarantee an acceptable level of occupancy comfort, to maintain good indoor air quality, and to minimize system costs and energy requirements. If failure data coming from company database are not available, then a reliability prediction based on failure rate model and handbook data must be carried out. Performing a reliability prediction provides an awareness of potential equipment degradation during the equipment life cycle. Otherwise, if field data regarding the component failures are available, then classical reliability assessment techniques such as Fault Tree Analysis and Reliability Block Diagram should be carried out. Reliability prediction of mechanical components is a challenging task that must be carefully assessed during the design of a system. For these reasons, this paper deals with the reliability assessment of an HVAC using both failure rate model for mechanical components and field data. The reliability obtained using the field data is compared to the one achieved using the failure rate models in order to assess a model which includes all the mechanical parts. The study highlights how it is fundamental to analyze the reliability of complex system integrating both field data and mathematical model.</p>

Mock circulatory loops used for testing cardiac assist devices: A review of computational and experimental models

Heart failure is a major health risk, and with limited availability of donor organs, there is an increasing need for developing cardiac assist devices (CADs). Mock circulatory loops (MCL) are an important in-vitro test platform for CAD’s performance assessment and optimisation. The MCL is a lumped parameter model constructed out of hydraulic and mechanical components aiming to simulate the native cardiovascular system (CVS) as closely as possible. Further development merged MCLs and numerical circulatory models to improve flexibility and accuracy of the system; commonly known as hybrid MCLs. A total of 128 MCLs were identified in a literature research until 25 September 2020. It was found that the complexity of the MCLs rose over the years, recent MCLs are not only capable of mimicking the healthy and pathological conditions, but also implemented cerebral, renal and coronary circulations and autoregulatory responses. Moreover, the development of anatomical models made flow visualisation studies possible. Mechanical MCLs showed excellent controllability and repeatability, however, often the CVS was overly simplified or lacked autoregulatory responses. In numerical MCLs the CVS is represented with a higher order of lumped parameters compared to mechanical test rigs, however, complex physiological aspects are often simplified. In hybrid MCLs complex physiological aspects are implemented in the hydraulic part of the system, whilst the numerical model represents parts of the CVS that are too difficult to represent by mechanical components per se. This review aims to describe the advances, limitations and future directions of the three types of MCLs.